Senior Solution Architect – Medical Devices

Remote from: Germany
Annual salary: Undisclosed
Salary information is not provided for this position. Check our Salary Directory to estimate the average compensation for similar roles.
Department: Healthcare & Medical
Employment type: Full Time,
Job posted: 26 May 2026
Apply before: 26 Jun 2026
Experience level: Senior
Views / Applies: 12 / 1

About company

About NVIDIA

NVIDIA is a leader in AI computing and graphics technology.

Computer Hardware
1993

Actively Hiring

AI Summary

NVIDIA seeks a Senior Solution Architect for Medical Devices to collaborate with medical device customers across EMEA, integrating AI and accelerated computing into next-generation healthcare products. The role involves designing proof-of-concept demonstrations, building strategic executive relationships, and optimizing workloads on NVIDIA's computing platform. Candidates need expertise in deep learning, medical imaging, and software development with C/C++, Python, or CUDA. The ideal candidate has 5+ years of experience in medical device industry, a strong technical background, and excellent communication skills. This position requires some travel and offers the opportunity to work on cutting-edge AI and accelerated computing technologies.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight This role demands deep expertise in AI, medical devices, and high-performance computing, along with strategic customer engagement and cross-functional leadership, making it highly challenging.

Salary Analysis

AI Insight The salary for this role is not specified, but based on market data for a Senior Solution Architect in medical devices at NVIDIA, the median is estimated at $220,000. This is competitive with top-tier tech companies, reflecting the specialized skill set and industry experience required.

Key Skills

AI Accelerated Computing Medical Devices Deep Learning Medical Imaging C/C++ Python CUDA Solution Architecture Healthcare

Cover Letter Sample

I am writing to express my interest in the Senior Solution Architect - Medical Devices position at NVIDIA. With a PhD in Biomedical Engineering and over 7 years of experience integrating AI into medical imaging and surgical systems, I am excited about the opportunity to advance healthcare through NVIDIA's accelerated computing platform.

In my previous role at a leading medical device company, I led the development of deep learning-based image analysis algorithms for real-time surgical guidance, resulting in a 30% improvement in procedure accuracy. I have extensive hands-on experience with CUDA, Python, and C++, and have successfully deployed AI models at the edge using NVIDIA Jetson platforms.

I am particularly drawn to NVIDIA's culture of innovation and collaboration. I look forward to leveraging my technical expertise and industry knowledge to help customers design next-generation software-defined medical devices and build strategic partnerships.

Thank you for considering my application. I am eager to discuss how my background aligns with the needs of your team and contribute to NVIDIA's mission of transforming healthcare with AI.

Possible Interview Questions

Describe your experience with integrating AI into medical devices. Can you provide a specific example of a project where you implemented deep learning for image analysis in a surgical or diagnostic setting?

In my previous role, I led a project to develop a real-time segmentation algorithm for laparoscopic surgery using NVIDIA's Clara platform. We trained a U-Net model on endoscopic video data and deployed it on an NVIDIA Jetson AGX Xavier, achieving sub-100ms inference time. This enabled surgeons to overlay organ boundaries during procedures, improving precision.

How do you approach optimizing deep learning models for edge deployment in medical devices? What trade-offs do you consider?

Optimizing for edge involves balancing accuracy, latency, and power consumption. I use techniques like quantization, pruning, and model distillation to reduce model size while maintaining clinical accuracy. For example, I converted a full-precision model to INT8 using TensorRT, which reduced latency by 4x with only a 1% drop in Dice score. I also consider regulatory requirements and ensure the optimized model is validated on representative datasets.

Can you explain how you would build a proof-of-concept demonstration for a medical device customer using NVIDIA's technology? Walk us through the steps.

First, I would understand the customer's clinical problem and technical requirements. Then I would design a solution architecture leveraging NVIDIA's hardware (e.g., Jetson for edge, A100 for cloud) and software stack (e.g., Clara, TensorRT, DeepStream). I'd develop a minimal viable prototype focusing on one key use case, such as real-time anomaly detection in X-ray images. After testing with customer data and iterating based on feedback, I would present the demo with clear metrics on performance and accuracy.

Describe a time you had to manage multiple priorities and projects simultaneously. How did you ensure successful outcomes?

At my previous job, I simultaneously led two customer engagements and an internal research project. I used Agile methodologies, maintaining a prioritized backlog and holding daily stand-ups. I communicated regularly with stakeholders to manage expectations and adjusted resources as needed. For example, I delegated the research project's data collection to a junior engineer while I focused on customer demos, ensuring all projects met their deadlines.

How do you stay current with the latest advancements in medical AI and accelerated computing? Can you give an example of a recent technology you've explored?

I regularly read papers from MICCAI and CVPR, and I'm an active member of NVIDIA's developer program. Recently, I explored diffusion models for medical image super-resolution. I implemented a prototype using MONAI and found it improved resolution of low-dose CT scans by 2x, which could reduce radiation exposure. I then shared my findings with colleagues via a tech talk.

At NVIDIA, we are advancing healthcare through innovation. As a Senior Solutions Architect for Medical Devices, you will collaborate with medical device customers, developers, scientists, and academic and industry leaders across EMEA to harness AI and accelerated computing.

NVIDIA’s Solution Architects are developers and scientists who apply the latest AI and accelerated computing technologies. Our machine learning, deep learning, and high-performance computing platforms are widely adopted across healthcare, including by medical device manufacturers, academic medical centers, pharmaceutical companies, and startups.

In this role, you will serve as a trusted technical advisor, helping customers integrate AI and accelerated computing at the edge and in the cloud. You will develop proof-of-concept demonstrations, build strategic executive relationships, and work with developers, researchers, data scientists, and IT leaders on impactful healthcare projects.

The ideal candidate is passionate about AI and accelerated computing in medical devices, has several years of medical device industry experience across research, technical project leadership, and product development, and enjoys cutting-edge technology and continuous learning.

What you will be doing:

Partner with our business/account team working with customers to develop a keen understanding of their goals, strategies, and technical needs and to help define and deliver high-value solutions meeting these needs.
Work to design NVIDIA’s HW/SW into next-generation software-defined medical devices, AI-enabled clinical applications, and advanced healthcare product platforms.
Stay up to date on the state of the art in medical image analysis, sensor processing, clinical AI, digital health, and surgical data science to apply the latest advancements in the field to customer needs.
Support customers to optimize workloads using NVIDIA’s computing platform.
Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard.
Partner strategically with lighthouse customers and industry-specific solution partners targeting our computing platform.
We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to find the best way to get your job done and make our customers successful.

What we need to see:

Strong foundational expertise: MS, PhD or equivalent experience in Computer Science, Mathematics, Biomedical Engineering, Electrical Engineering, or closely related fields.
5+ years of work-related experience in software development, machine learning, deep learning or high-performance computing.
In-depth knowledge and practical experience with contemporary Deep Learning software architecture and frameworks, in particular regarding image and video processing of medical and surgical modalities.
Experience in scientific computing and software development with C/C++, Python, or CUDA. Skilled in streaming data processing, performance analysis, and optimization from algorithms to pipelines.
Strong time-management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects.
Excellent communication skills particularly in the presentation of highly technical material. Must enjoy interacting with forward-thinking people, life-long learning, and staying at the forefront of the domain.

Ways to stand out from the crowd:

Domain expertise and proven hands-on experience applying accelerated computing and AI in one or more medical device areas, such as medical imaging, digital surgery, surgical data science, image-guided intervention, patient monitoring, or clinical workflow applications. Familiarity with clinical workflows, interventional and/or surgical procedures is a plus.
Several years of industry experience in the medical device development life cycle, including research, technical project leadership, product development, or developing software in regulated environments. Understanding of regulatory requirements (e.g., HIPAA) and data privacy concerns specific to healthcare data.
Extensive deep learning knowledge with practical experience in frameworks and model architectures (e.g., CNNs, LLMs, VLMs), medical image and video analysis, segmentation, detection, multimodal clinical AI, and training from simulation or Digital Twins. Proficiency in deploying AI models and optimizing inference using TensorRT, ONNX Runtime, Triton, or TensorRT-LLM is a plus.
Proven experience implementing and optimizing workloads with CUDA and Nsight Tools. Experience with high performance networking technologies, e.g. DPDK, DOCA, RMDA, RoCEv2 is a plus.
Published record of thought leadership in a technical area or industry segment.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re creative and autonomous, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

If you are passionate about NVIDIA technology and how it can unlock Healthcare or Life Sciences, we should talk!

Apply now >